We address the problem of estimating the uncertainty of pixel based image registration algorithms, given just the two images to be registered, for cases when no ground truth data is available. Our novel method uses bootstrap resampling. It is very general, applicable to almost any registration method based on minimizing a pixel-based similarity criterion; we demonstrate it using the SSD, SAD, correlation, and mutual information criteria. We show experimentally that the bootstrap method provides better estimates of the registration accuracy than the state-of-the-art CramEr-Rao bound method. Additionally, we evaluate also a fast registration accuracy estimation (FRAE) method which is based on quadratic sensitivity analysis ideas and has a negligible computational overhead. FRAE mostly works better than the CramEr-Rao bound method but is outperformed by the bootstrap method.
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Resurveying historical vegetation plots has become more and more popular in recent years as it provides a unique opportunity to estimate vegetation and environmental changes over the past decades. Most historical plots, however, are not permanently marked and uncertainty in plot location, in addition to observer bias and seasonal bias, may add significant error to temporal change. These errors may have major implications for the reliability of studies on long-term environmental change and deserve closer attention of vegetation ecologists. MATERIAL & METHODS: Vegetation data obtained from the resurveying of non-permanently marked plots are assessed for their potential to study environmental-change effects on plant communities and the challenges the use of such data have to meet. We describe the properties of vegetation resurveys distinguishing basic types of plots according to relocation error, and we highlight the potential of such data types for studying vegetation dynamics and their drivers. Finally, we summarise the challenges and limitations of resurveying non-permanently marked vegetation plots for different purposes in environmental change research. RESULTS AND CONCLUSIONS: Resampling error is caused by three main independent sources of error: error caused by plot relocation, observer bias, and seasonality bias. For relocation error, vegetation plots can be divided into permanent and non-permanent plots, while the latter are further divided into quasi-permanent (with approximate relocation) and non-traceable (with random relocation within a sampled area) plots. To reduce the inherent sources of error in resurvey data, the following precautions should be followed: (i) resurvey historical vegetation plots whose approximate plot location within a study area is known; (ii) consider all information available from historical studies in order to keep plot relocation errors low; (iii) resurvey at times of the year when vegetation development is comparable to the historical survey to control for seasonal variability in vegetation; (iv) keep a high level of experience of the observers to keep observer bias low; and (v) edit and standardise datasets before analyses.
AIM: Resurveys of historical vegetation plots are increasingly used for the assessment of decadal changes in plant species diversity and composition. However, historical plots are usually relocated only approximately. This potentially inflates temporal changes and undermines results. LOCATION: Temperate deciduous forests in Central Europe. METHODS: To explore if robust conclusions can be drawn from resurvey studies despite location uncertainty, we compared temporal changes in species richness, frequency, composition and compositional heterogeneity between exactly and approximately relocated plots. We hypothesized that compositional changes should be lower and changes in species richness should be less variable on exactly relocated plots, because pseudo-turnover inflates temporal changes on approximately relocated plots. RESULTS: Temporal changes in species richness were not more variable and temporal changes in species composition and compositional heterogeneity were not higher on approximately relocated plots. Moreover, the frequency of individual species changed similarly on both plot types. MAIN CONCLUSIONS: The resurvey of historical vegetation plots is robust to uncertainty in original plot location and, when done properly, provides reliable evidence of decadal changes in plant communities. This provides important background for other resurvey studies and opens up the possibility for large-scale assessments of plant community change.
- Keywords
- pseudo-turnover, resampling, revisitation, semi-permanent plots, temperate forest, temporal vegetation change,
- Publication type
- Journal Article MeSH
The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today's sensor spatial arrangement is inspired by our visual system. However, we have not come further than rigid rectangular and, on a minor scale, hexagonal sensor arrangements. Even in this situation, there is a need for directly assessing differences between the rectangular and hexagonal sensor arrangements, i.e., without the conversion of one arrangement to another. In this paper, we propose a method to create a common space for addressing any spatial arrangements and assessing the differences among them, e.g., between the rectangular and hexagonal. Such a space is created by implementing a continuous extension of discrete Weyl Group orbit function transform which extends a discrete arrangement to a continuous one. The implementation of the space is demonstrated by comparing two types of generated hexagonal images from each rectangular image with two different methods of the half-pixel shifting method and virtual hexagonal method. In the experiment, a group of ten texture images were generated with variational curviness content using ten different Perlin noise patterns, adding to an initial 2D Gaussian distribution pattern image. Then, the common space was obtained from each of the discrete images to assess the differences between the original rectangular image and its corresponding hexagonal image. The results show that the space facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements by which, in the experiment, the hexagonal images show richer intensity variation, nonlinear behavior, and larger dynamic range in comparison to the rectangular images.
- Keywords
- common space, continuous extension, hexagonal image, pixel arrangement, pixel form, resampling, software-based,
- Publication type
- Journal Article MeSH
Respiratory sinus arrhythmia (RSA) is an index of cardiovagal regulation, emotional and cognitive processing. RSA is quantified using heart rate variability (HRV) spectral analysis at respiratory-linked high-frequency band (HF-HRV) using Fast Fourier transformation (FFT) or autoregressive (AR) method, both requiring resampling of recordings - a potential source of error. We hypothesized that rarely used HRV time-frequency analysis with Lomb-Scargle periodogram (LSP) without resampling could be more sensitive to detect neurocardiac response to posture change than FFT and AR. Orthostasis (posture change from supine to standing) evoked significant decrease of HF-HRV well detectable by FFT, AR, and LSP. In contrast, during posture change from sitting to lying, significant increase of HF-HRV and peak HF was best detected using LSP. In regression analysis, the associations between RR-interval, HF-HRV, and peak HF were best detected when evaluated using LSP. Time-frequency HRV analysis with LSP could represent an important alternative to conventional FFT and AR methods for assessment of cardiovagal regulation indexed by RSA.
- Keywords
- Cardiovagal regulation, Heart rate variability analysis, Lomb-Scargle periodogram, Orthostatic test, Respiratory sinus arrhythmia, Spectral analysis,
- MeSH
- Time Factors MeSH
- Respiratory Rate physiology MeSH
- Electrocardiography MeSH
- Fourier Analysis MeSH
- Humans MeSH
- Adolescent MeSH
- Statistics, Nonparametric MeSH
- Regression Analysis MeSH
- Respiratory Sinus Arrhythmia physiology MeSH
- Heart Rate physiology MeSH
- Check Tag
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
We examined how penalized linear discriminant analysis with resampling, which is a supervised, multivariate, whole-brain reduction technique, can help schizophrenia diagnostics and research. In an experiment with magnetic resonance brain images of 52 first-episode schizophrenia patients and 52 healthy controls, this method allowed us to select brain areas relevant to schizophrenia, such as the left prefrontal cortex, the anterior cingulum, the right anterior insula, the thalamus, and the hippocampus. Nevertheless, the classification performance based on such reduced data was not significantly better than the classification of data reduced by mass univariate selection using a t-test or unsupervised multivariate reduction using principal component analysis. Moreover, we found no important influence of the type of imaging features, namely local deformations or gray matter volumes, and the classification method, specifically linear discriminant analysis or linear support vector machines, on the classification results. However, we ascertained significant effect of a cross-validation setting on classification performance as classification results were overestimated even though the resampling was performed during the selection of brain imaging features. Therefore, it is critically important to perform cross-validation in all steps of the analysis (not only during classification) in case there is no external validation set to avoid optimistically biasing the results of classification studies.
A method for random resampling of time series from multiscale processes is proposed. Bootstrapped series--realizations of surrogate data obtained from random cascades on wavelet dyadic trees--preserve the multifractal properties of input data, namely, interactions among scales and nonlinear dependence structures. The proposed approach opens the possibility for rigorous Monte Carlo testing of nonlinear dependence within, with, between, or among time series from multifractal processes.
- Publication type
- Journal Article MeSH
Computer simulations of biomolecules such as molecular dynamics often suffer from insufficient sampling. Due to limited computational resources, insufficient sampling prevents obtaining proper equilibrium distributions of observed properties. To deal with this problem, we proposed a simulation protocol for efficient resampling of collected off-equilibrium trajectories. These trajectories are utilized for the initial mapping of the conformational space, which is later properly resampled by the introduced Iterative Landmark-Based Umbrella Sampling (ILBUS) method. Reconstruction of static equilibrium properties is achieved by the multistate Bennett acceptance ratio (MBAR) method, which enables efficient use of simulated data. The ILBUS protocol is geometry-based and does not demand any additional collective variable or a dimensional-reduction technique. The only requirement is a set of suitably spaced reference conformations, which serve as landmarks in the mapped conformational space. Additionally, the ILBUS protocol encompasses an iterative process that optimizes the force constant used in the umbrella sampling simulation. Such tuning is an inherent feature of the protocol and does not need to be performed by the user in advance. Furthermore, even the simulations with suboptimal force constants can be used in estimates by MBAR. We demonstrate the feasibility and the performance of this approach in the study of the conformational landscape of the alanine dipeptide, met-enkephalin, and adenylate kinase.
- MeSH
- Adenylate Kinase * MeSH
- Alanine MeSH
- Dipeptides chemistry MeSH
- Enkephalin, Methionine MeSH
- Molecular Dynamics Simulation * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Adenylate Kinase * MeSH
- Alanine MeSH
- Dipeptides MeSH
- Enkephalin, Methionine MeSH
Although spatial and temporal variation are both important components structuring microbial communities, the exact quantification of temporal turnover rates of fungi and bacteria has not been performed to date. In this study, we utilised repeated resampling of bacterial and fungal communities at specific locations across multiple years to describe their patterns and rates of temporal turnover. Our results show that microbial communities undergo temporal change at a rate of 0.010-0.025 per year (in units of Sorensen similarity), and the change in soil is slightly faster in fungi than in bacteria, with bacterial communities changing more rapidly in litter than soil. Importantly, temporal development differs across fungal guilds and bacterial phyla with different ecologies. While some microbial guilds show consistent responses across regional locations, others show site-specific development with weak general patterns. These results indicate that guild-level resolution is important for understanding microbial community assembly, dynamics and responses to environmental factors.
- Keywords
- bacteria, community assembly, forest, fungi, soil, temporal turnover,
- MeSH
- Fungi MeSH
- Microbiota * MeSH
- Mycobiome * MeSH
- Soil MeSH
- Soil Microbiology MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Soil MeSH
The ISO 15189:2012 standard section 5.9.1 requires laboratories to review results before release, considering quality control, previous results, and clinical information, if any, and to issue documented procedures about it. While laboratory result reporting is generally regarded as part of the post-analytical phase, the result release process requires a general view of the total examination process. Reviewing test results may follow with troubleshooting and test repetition, including reanalyzing an individual sample or resampling. A systematic understanding of the result release may help laboratory professionals carry out appropriate test repetition and ensure the plausibility of laboratory results. In this paper, we addressed the crucial steps in the result release process, including evaluation of sample quality, critical result notification, result reporting, and recommendations for the management of the result release, considering quality control alerts, instrument flags, warning messages, and interference indexes. Error detection tools and plausibility checks mentioned in the present paper can support the daily practice of results release.
- Keywords
- Accreditation, ISO 15,189, Laboratory errors, Quality control, Result release,
- MeSH
- Accreditation * MeSH
- Clinical Laboratory Techniques MeSH
- Laboratories * MeSH
- Humans MeSH
- Quality Control MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
